Auxiliary function for Ameva algorithm
This function is required to compute the ameva value for Ameva algorithm.
ameva(tb)
tb |
a vector of observed frequencies, k*l |
This function implements the Ameva criterion proposed in Gonzalez-Abril, Cuberos, Velasco and Ortega (2009) for Discretization. An autonomous discretization algorithm(Ameva) implements in disc.Topdown(data,method=1)
It uses a measure based on chi^2 as the criterion for the optimal discretization which has the minimum number of discrete intervals and minimum loss of class variable interdependence. The algorithm finds local maximum values of Ameva criterion and a stopping criterion.
Ameva coefficient is defined as follows:
Ameva(k)=\frac{χ^2(k)}{k*(l-1)}
for k, l >=2, k is a number of intervals, l is a number of classes.
This value calculates in contingency table between class variable and discrete interval, row matrix representing the class variable and each column of discrete interval.
val |
numeric value of Ameva coefficient |
HyunJi Kim polaris7867@gmail.com
Gonzalez-Abril, L., Cuberos, F. J., Velasco, F. and Ortega, J. A. (2009) Ameva: An autonomous discretization algorithm, Expert Systems with Applications, 36, 5327–5332.
disc.Topdown,
topdown,
insert,
findBest and
chiSq.
#--Ameva criterion value a=c(2,5,1,1,3,3) m=matrix(a,ncol=3,byrow=TRUE) ameva(m)
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